Internet of Things and Ubiquitous Sensing

A pillar of the Future Internet, the Internet of Things (IoT) will comprise many billions of Internet-connected objects (ICOs) or "things" that can sense, communicate, compute, and potentially actuate, as well as have intelligence, multimodal interfaces, physical/virtual identities, and attributes. The IoT incorporates concepts from pervasive, ubiquitous, and ambient computing, which have been evolving since the late '90s and have now reached some level of maturity. It fuses the digital and physical worlds by bringing different concepts and technical components together. Along with the World Wide Web and mobility, IoT potentially represents the most disruptive technological revolution to date. With billions of ICOs and a diverse abundance of sensors, the IoT will be an enabler of ubiquitous sensing.

The IoT Vision

The term Internet of Things was first coined by Kevin Ashton in a presentation in 1999. As he stated, "the Internet of Things has the potential to change the world, just as the Internet did -- maybe even more so." The IoT has since become the focus of multiple efforts by standards organizations, including the International Telecommunication Union (ITU), which is at the forefront of global standards development. The IoT will enable hitherto unknown and unimagined forms of collaboration and communication between people and things, and between things themselves. ITU's Telecommunication Standardization Sector (ITU-T) and its membership firmly believe that the IoT's success depends strongly on the existence and smooth and effective operation of global standards, as evidenced by the ongoing work carried out by the group "Internet of Things Global Standards Initiative (IoT-GSI)."

The IoT vision encompasses a significant amount of existing and evolving technologies that drive it. Harald Sundmaeker and his colleagues listed a comprehensive set of those technologies in their March 2010 report, "Vision and Challenges for Realising the Internet of Things." They included technologies for identification, IoT architecture, service-oriented-architecture, communications (Bluetooth, ZeegBee, and so on), cognitive radios, network discovery, data and signal processing, data discovery and search, power and energy storage, security and privacy, and many others.

The IoT has garnered substantial attention through the European Framework Program (EU FP7), as well as programs in the US and Southeast Asia. The vision is very broad and grand, as illustrated by the following definition from Patrick Guillemin and Peter Friess: "The Internet of Things allows people and things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service." IoT is also expected to play a significant role in the ambitious forthcoming European research program "Horizon-2020," which will define the European research agenda for next 7-10 years.

Analysts expect that 50 to 100 billion devices will be connected to the Internet by 2020. According to a BCC Research report, the global market for sensors was about US$56.3 billion in 2010 and about $62.8 billion in 2011. The global market for sensors is expected to increase to $91.5 billion by 2016, showing a compound annual growth rate of 7.8 percent.

The IoT will be a major source of big data, contributing massive amounts of streamed information from billions of ICOs. Typical IoT applications that produce big data include meteorology, experimental physics, astronomy, biology, and environmental science. For example, a Boeing jet generates 10 TBytes of data per engine every 30 minutes. A single six-hour flight would thus generate some 240 TBytes of data -- and there are about 28,537 commercial flights in the US skies on any given day. An A380 has more than 300,000 sensors on board constantly generating data streams. Clearly, machine-to-machine (M2M) communications will generate enormous amounts of Internet traffic leading to Zettabyte science.

Theme Articles

The IoT generates not only excitement, enthusiasm, and technology euphoria but also caution and a call to soberly analyse IoT-inspired challenges. This month's Computing Now theme begins with Vinton Cerf's IEEE Internet Computing column, "Things and the Net." In it, Cerf examines some of the potential complexity, deployment, and maintenance challenges of massively distributed and heterogeneous "things," as well as grand challenges related to security and privacy. It is encouraging to see that Google takes IoT seriously.

Gerd Kortuem and colleagues address a very important aspect of the emerging IoT paradigm -- namely, how to educate and prepare future generations of developers, architects, and users. Their article, "Educating the Internet-of-Things Generation," talks about the Open University's My Digital Life course, which offers an educational infrastructure for learning about and experimenting with IoT technologies. It is indeed important to offer online IoT education to potentially large numbers of current and future users who will be thinkers and champions of future technologies.

The availability of massive amounts of information streaming from billions of IoT devices inevitably and justly generates security and privacy concerns. Huansheng Ning and colleagues' "Cyberentity Security in the Internet of Things" then discusses security attacks, vulnerabilities, and countermeasures in the IoT and offers a generic multilayer architecture for protecting IoT cyberentities.

In a world that's saturated with "things" that form diverse and heterogeneous networks with overlapping capabilities in massively distributed IoT-based systems, it's important to efficiently utilize resources, including power efficiency, sensor data repurposing, and sharing. To that end, sensors and applications that use them must be decoupled, thus making it crucial to develop discovery mechanisms that let applications, systems, and services discover and capture relevant data -- either from cloud-based sensor data repositories or from live sensors deployed by different vendors. "Context-Aware Sensor Search, Selection, and Ranking Model for Internet of Things Middleware," by Charith Perera and colleagues, explores this topic and proposes a way to discover and use sensors and sensor data streams in IoT applications. Part of the EU FP7-sponsored OpenIoT project, their discovery mechanism is based on the Semantic Sensor Network ontology and annotated sensor data. Use cases of that project include digital agriculture, smart cities, environmental monitoring, and intelligent manufacturing. The following videos illustrate some of these use cases. (You can view others at the OpenIoT YouTube channel.)

To realize the IoT vision of bringing technology to people anytime, anywhere, with any device, service, or application, not only must users be aware of their device capabilities but the "things" must also be aware of users' activities, preferences, and context. The article "Opportunistic Human Activity and Context Recognition," by Daniel Roggen and colleagues, aims at achieving true ambient intelligence using human-activity recognition methods that can themselves dynamically adapt to captured and discovered sensor data. The article also presents lessons learned and concludes on the optimistic note that ambient intelligence systems are feasible in near future.

Coming Soon

The articles in this month's theme address several important challenges that the Internet of Things raises and propose solutions that will make the IoT feasible, deployable, and usable. Of course, more research and many more challenges must be resolved before the vision becomes a reality, but it will likely become a feature of everyday life within the next five to seven years. I encourage interested readers to do further research and to join the growing community of practice of IoT champions, researchers, developers, architects, and users.

Arkady Zaslavsky is senior principal research scientist, science leader at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia. He is also an adjunct professor at Australian National University, University of New South Wales, and Luleå University of Technology, Sweden. He has a PhD in computer science from the Institute for Control Sciences (IPU-IAT), USSR Academy of Sciences. His technical interests focus on pervasive, ubiquitous, and mobile computing; context-awareness; semantic data management; and the Internet of Things. Zaslavsky is a member of the CN editorial board. Contact him at arkady.zaslavsky@csiro.au.

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